title: A competing risks approach for nonparametric estimation of transition probabilities in a non-Markov illness-death model.
abstract: Competing risks model time to first event and type of first event. An example from hospital epidemiology is the incidence of hospital-acquired infection, which has to account for hospital discharge of non-infected patients as a competing risk. An illness-death model would allow to further study hospital outcomes of infected patients. Such a model typically relies on a Markov assumption. However, it is conceivable that the future course of an infected patient does not only depend on the time since hospital admission and current infection status but also on the time since infection. We demonstrate how a modified competing risks model can be used for nonparametric estimation of transition probabilities when the Markov assumption is violated.
authors.affiliation: Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany, arthur.allignol@fdm.uni-freiburg.de.
authors.forename: Arthur
authors.initials: A
authors.lastname: Allignol
authors.forename: Jan
authors.initials: J
authors.lastname: Beyersmann
authors.forename: Thomas
authors.initials: T
authors.lastname: Gerds
authors.forename: Aurélien
authors.initials: A
authors.lastname: Latouche
mesh_terms: D003198:Computer Simulation; D003428:Cross Infection / Q000453:epidemiology* / Q000401:mortality / Q000635:transmission; D006801:Humans; D053208:Kaplan-Meier Estimate; D015993:Life Tables; D008390:Markov Chains; D015233:Models, Statistical; D011336:Probability; D012306:Risk; D018709:Statistics, Nonparametric; D013269:Stochastic Processes; D016019:Survival Analysis